Video Coding With CABAC Motion Predictor Index Segmentation
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Solution Overview
Problem
The existing video coding standards, such as HEVC, face challenges in efficiently encoding and decoding motion vectors due to the complexity and inefficiency of tools like affine motion mode and Alternative Temporal Motion Vector Prediction (ATMVP), particularly in handling complex motions and increased coding complexity.
Innovation Solution
Implement methods and devices for encoding and decoding motion vector predictor indices using Context Adaptive Binary Arithmetic Coding (CABAC) with techniques like bypass coding, shared contexts, and context variables based on neighboring blocks to optimize the encoding and decoding processes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If ATMVP is enabled at SPS level to increase the number of Merge candidates, then coding efficiency for complex motions is improved, but device complexity increases due to additional candidates and context variables
Solution Approach 1:
The patent segments the Merge candidate list into different types (spatial candidates, temporal candidates, and ATMVP candidates) with different coding methods. Spatial candidates use one context variable while temporal and ATMVP candidates use another context variable, allowing selective processing and reducing overall complexity despite having more candidates.
Solution Approach 2:
Different context variables are assigned to different types of Merge candidates based on their local characteristics. The patent applies local quality by using context variable 1 for spatial candidates and context variable 2 for temporal/ATMVP candidates, optimizing the coding process for each candidate type's specific probability distribution.
2Measurement precision
If the number of Merge candidates is increased to include ATMVP, then motion prediction accuracy is improved, but the complexity of encoding and decoding the Merge index increases
Solution Approach 1:
The patent segments the Merge index coding process into different parts with different coding methods. The first part (spatial candidates) uses one set of context variables while the second part (temporal and ATMVP candidates) uses another set, reducing the complexity of processing each segment individually.
Solution Approach 2:
The patent dynamically adjusts the coding process based on the candidate type being processed. The context variable selection changes based on whether the current candidate is spatial, temporal, or ATMVP, allowing the system to adapt to different prediction scenarios and reduce overall complexity.
3Measurement precision
If affine motion mode is used to handle complex motions, then motion compensation accuracy is improved, but device complexity increases
Solution Approach 1:
The patent segments the motion prediction process into different modes (spatial prediction, temporal prediction, ATMVP, and affine motion). Each mode is handled with appropriate context variables and coding methods, allowing the system to use complex affine transforms only when necessary while keeping simpler modes available for less complex scenarios.
Data Source
AI summary
A method of encoding information about a motion information predictor, comprising: selecting one of a plurality of motion information predictor candidates; and encoding information for identifying the selected motion information predictor candidate using CABAC coding, wherein the CABAC coding comprises, for at least one bit of said information, using the same context variable used for another inter prediction mode when one or both of a Triangle Merge mode or a Merge with Motion Vector Difference (MMVD) Merge mode is used.